A neurodynamic algorithm for solving demand response problem of residential consumer with electric vehicle

摘要

#$%^&*AU2019100860A420190912.pdf#####Abstract With the development of industry, factories and vehicles produce excessive greenhouse gases, which causes serious environmental pollution. Moreover, the scarcity of petroleum energy is also a serious problem demanding prompt solution. The application of plug-in electric vehicles (PEVs) and photovoltaic power system alleviates the problem of energy shortage. Thus, the popularity of smart grid and related topics is exploded and the situation of PEVs and power grid were analyzed. Based on the widely using of PEVs, there is no doubt that how to minimize the electricity cost of users is also a question worth probing into. Therefore, demand response (DR) problem plays an important role in smart grid because of the using of the communication of consumers and the utility and is discussed universally. DR means that when the price of the utility increases, consumers adjust their electric strategy after receiving the information of power price increasing from the inductive reduction load sent by the power supplier.Energy information grid Base load I Domestic user -PV system 1AMI PEV _ I Figure 1: The framework of domestic consumer model. Initial variables, i=0,#=1 (Ec (t), Ed (t),6(t), A1 |r T Neurodynamic algorithm(1 6) = 0? NO A) =,Ak+ V4 YES -# +0. 1 tNOi5 YES Output optimal variables Figure 2: The execution of proposed algorithm